TEL AVIV, ISRAEL--(Marketwire - Mar 28, 2012) - Jinni, the creator of the first and only taste and mood-based discovery engine for movies and TV programming, today announced the new version release of its API for TV operators and consumer electronics (CE) manufacturers. Leveraging the benefits of Jinni's core technology, the new API offers advanced personalization features across all catalogs, including live broadcast TV, powered by the Jinni Entertainment Genome™ as well as delivers new "effective social" capabilities. The result is a grid-less, schedule-less TV guide and a more user-centric entertainment experience.
Jinni's API enables TV operators, manufacturers of connected devices and large catalog owners to build their own intuitive guides, driven by content semantics and the viewer's tastes. Thanks to the seamless integration capabilities, and rich set of features designed for both lean-back and lean-forward TV viewing, consumers can enjoy pre-selected content recommendations. All features can be tested by customers and partners using Jinni's 'sandbox' capability which provides easy and fast prototyping, thus enabling product and UI teams to test and explore all Jinni features.
"Jinni is transforming the way users select TV programming by discovering and delivering content that is tailored to meet a person's mood or taste. This makes the TV guide as we know it, and the grid in particular, a thing of the past," said Yosi Glick, Jinni Co-Founder & CEO. With the new API version, TV operators and CE manufacturers can now provide their customers with a more intuitive experience across various entertainment platforms, including live broadcasting, and enjoy the easy incorporation into existing platforms."
The new API version also offers the traditional Jinni features, like the Taste Profile, which presents a number of defined Taste Channels that are automatically created based on viewing habits and consumption history. For a true lean-back experience, operators and manufacturers can create a personal 'comfort zone' for their subscribers, where titles from linear, VOD and OTT catalogs reflect the viewer's personal taste. For example, a viewer's Taste Profile can reflect their interest in stories about clever criminal heroes or towards cynical family relations, depending on their mood.
The engine can also cross reference a number of Taste Profiles, resulting in shared content recommendations. The "Watch Together" feature can be used (i) in households with multiple viewers, where Jinni will adapt according to those present and provide titles that are suitable and enjoyable for all; and (ii) for tapping into a social experience and enabling shared recommendations among social media connections. The API also offers a "neighbors" feature which allows viewers to turn to others for content suggestions. This feature goes beyond the standard known integration of leading social networks, which provides a glimpse at what all connected friends are watching. Neighbors expose the viewer only to the shared content that fits their Taste Profile - eliminating social clutter.
For the more "active" viewer, interested in finding the perfect content on their own, Jinni has developed intuitive browsing and search tools which allow the viewer to explore and discover different types of available entertainment content using the remote or by enabling voice control. This is Jinni's answer to random channel zapping and is one of the features supported by the Entertainment Genome™ that enables users to define and refine their content by mood, plot, audience, time period, and more. Now there is no need to endlessly flip through VOD catalog pages of "drama", "action" or "romance." With the Jinni API, viewers will be able to browse or search for content as they think or speak, by using natural metaphors. To date, customers who have already utilized the Jinni API within their products and services include two Tier-1 US cable operators, Microsoft, Rovi for Best Buy, and European IPTV operator Belgacom.
About Jinni Media
Jinni is the first and only taste-and-mood based engine powering video discovery. Using content genetics and nuanced understanding of user tastes, the Jinni engine powers a uniquely intuitive, personalized experience that increases content consumption and reduces churn. The Jinni service is powered by the Entertainment Genome™, containing thousands of genes that are assigned to each title to describe mood, style, plot, setting and more; this is a rich alternative to the usual genre language. New titles are automatically indexed via analysis of user reviews and synopses, using a proprietary Natural Language Processing solution.
Jinni's content discovery solution has been voted "Best Product Idea" by CableLabs. Jinni is a Webby Awards honoree, a Red Herring 100 Europe winner, an OnHollywood 100 winner, a SXSW Web Awards nominee, a TechCrunch Europas nominee and was selected as the best movie recommendation engine by CNET and Lifehacker. To see Jinni's award winning engine at work, visit www.jinni.com.